A new methodology is proposed to investigate information processing of complex, auditory patterns by normal-hearing listeners. In this procedure, each auditory pattern represents a randomly selected sample of values of some acoustic parameter. In a simple case, for example, the patterns might be tone sequences with randomly selected frequencies. The listeners task is to discriminate target from nontarget patterns based on a average difference in the values of the sampled parameter. By definition, the uncertainty associated with the random variation in patterns is a source of information. The listener must process this information in order to perform the sample-discrimination. Sample-discrimination experiments are proposed for a variety of auditory patterns of increasing complexity. Listener performance is expressed relative to that of a theoretical ideal observer to permit comparisons across experiments. Also, trial-by-trial analyses are proposed to provide tests of specific hypotheses regarding how listeners utilize the information in these patterns. The results of these analyses will allow answers to questions regarding how the detection and discrimination of complex auditory patterns is affected by information processing capacity, information weighting, and interference both within and across stimulus dimensions. As a long term goal of the project, experimental results will be used to develop a computational model for determining how best to package the acoustic information in patterns so as to maximize information transmission.